mirror of
https://github.com/leejet/stable-diffusion.cpp.git
synced 2026-07-23 11:20:53 -05:00
feat: support for --tensor-type-rules on generation modes (#932)
This commit is contained in:
87
model.cpp
87
model.cpp
@@ -1254,15 +1254,59 @@ std::map<ggml_type, uint32_t> ModelLoader::get_vae_wtype_stat() {
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return wtype_stat;
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}
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void ModelLoader::set_wtype_override(ggml_type wtype, std::string prefix) {
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static std::vector<std::pair<std::string, ggml_type>> parse_tensor_type_rules(const std::string& tensor_type_rules) {
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std::vector<std::pair<std::string, ggml_type>> result;
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for (const auto& item : split_string(tensor_type_rules, ',')) {
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if (item.size() == 0)
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continue;
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std::string::size_type pos = item.find('=');
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if (pos == std::string::npos) {
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LOG_WARN("ignoring invalid quant override \"%s\"", item.c_str());
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continue;
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}
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std::string tensor_pattern = item.substr(0, pos);
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std::string type_name = item.substr(pos + 1);
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ggml_type tensor_type = GGML_TYPE_COUNT;
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if (type_name == "f32") {
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tensor_type = GGML_TYPE_F32;
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} else {
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for (size_t i = 0; i < GGML_TYPE_COUNT; i++) {
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auto trait = ggml_get_type_traits((ggml_type)i);
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if (trait->to_float && trait->type_size && type_name == trait->type_name) {
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tensor_type = (ggml_type)i;
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}
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}
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}
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if (tensor_type != GGML_TYPE_COUNT) {
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result.emplace_back(tensor_pattern, tensor_type);
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} else {
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LOG_WARN("ignoring invalid quant override \"%s\"", item.c_str());
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}
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}
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return result;
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}
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void ModelLoader::set_wtype_override(ggml_type wtype, std::string tensor_type_rules) {
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auto map_rules = parse_tensor_type_rules(tensor_type_rules);
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for (auto& [name, tensor_storage] : tensor_storage_map) {
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if (!starts_with(name, prefix)) {
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ggml_type dst_type = wtype;
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for (const auto& tensor_type_rule : map_rules) {
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std::regex pattern(tensor_type_rule.first);
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if (std::regex_search(name, pattern)) {
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dst_type = tensor_type_rule.second;
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break;
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}
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}
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if (dst_type == GGML_TYPE_COUNT) {
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continue;
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}
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if (!tensor_should_be_converted(tensor_storage, wtype)) {
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if (!tensor_should_be_converted(tensor_storage, dst_type)) {
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continue;
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}
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tensor_storage.expected_type = wtype;
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tensor_storage.expected_type = dst_type;
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}
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}
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@@ -1603,41 +1647,6 @@ bool ModelLoader::load_tensors(std::map<std::string, struct ggml_tensor*>& tenso
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return true;
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}
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std::vector<std::pair<std::string, ggml_type>> parse_tensor_type_rules(const std::string& tensor_type_rules) {
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std::vector<std::pair<std::string, ggml_type>> result;
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for (const auto& item : split_string(tensor_type_rules, ',')) {
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if (item.size() == 0)
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continue;
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std::string::size_type pos = item.find('=');
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if (pos == std::string::npos) {
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LOG_WARN("ignoring invalid quant override \"%s\"", item.c_str());
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continue;
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}
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std::string tensor_pattern = item.substr(0, pos);
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std::string type_name = item.substr(pos + 1);
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ggml_type tensor_type = GGML_TYPE_COUNT;
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if (type_name == "f32") {
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tensor_type = GGML_TYPE_F32;
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} else {
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for (size_t i = 0; i < GGML_TYPE_COUNT; i++) {
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auto trait = ggml_get_type_traits((ggml_type)i);
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if (trait->to_float && trait->type_size && type_name == trait->type_name) {
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tensor_type = (ggml_type)i;
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}
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}
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}
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if (tensor_type != GGML_TYPE_COUNT) {
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result.emplace_back(tensor_pattern, tensor_type);
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} else {
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LOG_WARN("ignoring invalid quant override \"%s\"", item.c_str());
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}
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}
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return result;
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}
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bool ModelLoader::tensor_should_be_converted(const TensorStorage& tensor_storage, ggml_type type) {
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const std::string& name = tensor_storage.name;
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if (type != GGML_TYPE_COUNT) {
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